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Sr Python Developer

Echo IT Solutions · Dallas, TX

About Echo IT Solutions

141 open jobs
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Sr Python Developer at Echo IT Solutions. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

  • Designed and led delivery of a Bedrock-based agentic support platform — tool-calling agents over a curated skill library with SSE streaming — that now handles 40M+ requests/month and deflects 61% of tier-1 support tickets, reducing median time-to-resolution from 34 minutes to 7
  • Designed the skill library abstraction — versioned, permission-scoped troubleshooting capabilities the agent composes at runtime — allowing new diagnostic workflows to ship without model or prompt-layer changes.
  • Configured Bedrock Guardrails and Knowledge Bases to enforce tenant-scoped grounding and output constraints, ensuring one tenant's telemetry and runbooks could never surface in another's session across a ~80-tenant fleet.
  • Owned provisioned throughput sizing and inference cost tuning, modeling peak concurrency against committed capacity to hold unit cost predictable as the fleet scaled.
  • Built the retrieval layer as hybrid search over self-managed Elasticsearch (BM25) and Aurora PostgreSQL, pgvector (dense), tuning chunking and re-ranking against a labeled relevance set rather than eyeballed examples.
  • Cut generative inference spend 58% ($2.1M annualized) by introducing Model-Tiering (routing 78% of traffic to smaller models via a learned classifier), prompt caching, and reserved provisioned throughput for peak windows — without measurable regression on the eval suite.
  • Architected and managed data warehousing solutions using Python, Azure Synapse Analytics and Snowflake, optimizing data partitioning, indexing and transformation pipelines for high-performance querying
  • Monitored Snowflake performance and query optimization using Python scripts and Snowflake's INFORMATION_SCHEMA views.
  • Designed and implemented GenAI-powered ETL pipelines using AWS Glue, Apache Airflow and Pandas, enabling automated KYC validation, risk profiling and suspicious transaction monitoring (CTR & SAR submissions to FINCEN) by leveraging GPT-based document parsing.
  • Implemented MLOps pipelines integrating DynamoDB and S3 for scalable feature engineering and training datasets.
  • Designed and integrated Agentic AI frameworks with Java-based microservices to enable autonomous task execution, decision-making, and workflow orchestration.
  • Integrated React frontend with Python-based REST APIs (Flask/FastAPI/Django) for real-time data exchange.
  • Created end-to-end test suites for Lang Graph workflows, validating correct node transitions, memory management, and stateful logic.

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